ArticleBrain sciences2023
Screening Children's Intellectual Disabilities with Phonetic Features, Facial Phenotype and Craniofacial Variability Index.
Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Voice as a predictive signal: protocol for a scoping review of AI in early childhood development.BMJ open · 2026Article
- The Adaptation of the Wechsler Intelligence Scale for Children-5th Edition (WISC-V) for Indonesia: A Pilot Study.Journal of Intelligence · 2025Article
- Voice as a Biomarker of Pediatric Health: A Scoping Review.Children (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntellectual Disability (ID) is a kind of developmental deficiency syndrome caused by congenital diseases or postnatal events. This syndrome could be intervened as soon as possible if its early screening was efficient, which may improve the condition of patients and enhance their self-care ability. The early screening of ID is always achieved by clinical interview, which needs in-depth participation of medical professionals and related medical resources.
methodsA new method for screening ID has been proposed by analyzing the facial phenotype and phonetic characteristic of young subjects. First, the geometric features of subjects' faces and phonetic features of subjects' voice are extracted from interview videos, then craniofacial variability index (CVI) is calculated with the geometric features and the risk of ID is given with the measure of CVI. Furthermore, machine learning algorithms are utilized to establish a method for further screening ID based on facial features and phonetic features.
resultsThe proposed method using three feature sets, including geometric features, CVI features and phonetic features was evaluated. The best performance of accuracy was closer to 80%.
conclusionsThe results using the three feature sets revealed that the proposed method may be applied in a clinical setting in the future after continuous improvement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.